85 citations · 202 across the 15 of their papers we have counts for
16 papers
Learning Agile Striker Skills for Humanoid Soccer Robots from Noisy Sensory Input
Zifan Xu, Myoungkyu Seo, Dongmyeong Lee +8
Learning fast and robust ball-kicking skills is a critical capability for humanoid soccer robots, yet it remains a challenging problem due to the need for rapid leg swings, postura…
L3M+P: Lifelong Planning with Large Language Models
Krish Agarwal, Yuqian Jiang, Jiaheng Hu +2
By combining classical planning methods with large language models (LLMs), recent research such as LLM+P has enabled agents to plan for general tasks given in natural language. How…
TeleMoMa: A Modular and Versatile Teleoperation System for Mobile Manipulation
Shivin Dass, Wensi Ai, Yuqian Jiang +6
A critical bottleneck limiting imitation learning in robotics is the lack of data. This problem is more severe in mobile manipulation, where collecting demonstrations is harder tha…
Symbolic State Space Optimization for Long Horizon Mobile Manipulation Planning
Xiaohan Zhang, Yifeng Zhu, Yan Ding +4
In existing task and motion planning (TAMP) research, it is a common assumption that experts manually specify the state space for task-level planning. A well-developed state space…
LLM+P: Empowering Large Language Models with Optimal Planning Proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang +4
Large language models (LLMs) have demonstrated remarkable zero-shot generalization abilities: state-of-the-art chatbots can provide plausible answers to many common questions that…
Language-Informed Transfer Learning for Embodied Household Activities
Yuqian Jiang, Qiaozi Gao, Govind Thattai +1
For service robots to become general-purpose in everyday household environments, they need not only a large library of primitive skills, but also the ability to quickly learn novel…
Temporal-Logic-Based Reward Shaping for Continuing Reinforcement Learning Tasks
Yuqian Jiang, Sudarshanan Bharadwaj, Bo Wu +3
In continuing tasks, average-reward reinforcement learning may be a more appropriate problem formulation than the more common discounted reward formulation. As usual, learning an o…
Deep R-Learning for Continual Area Sweeping
Rishi Shah, Yuqian Jiang, Justin Hart +1
Coverage path planning is a well-studied problem in robotics in which a robot must plan a path that passes through every point in a given area repeatedly, usually with a uniform fr…
Solving Service Robot Tasks: UT Austin Villa@Home 2019 Team Report
Rishi Shah, Yuqian Jiang, Haresh Karnan +8
RoboCup@Home is an international robotics competition based on domestic tasks requiring autonomous capabilities pertaining to a large variety of AI technologies. Research challenge…
Desiderata for Planning Systems in General-Purpose Service Robots
Nick Walker, Yuqian Jiang, Maya Cakmak +1
General-purpose service robots are expected to undertake a broad range of tasks at the request of users. Knowledge representation and planning systems are essential to flexible aut…
Improving Grounded Natural Language Understanding through Human-Robot Dialog
Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov +6
Natural language understanding for robotics can require substantial domain- and platform-specific engineering. For example, for mobile robots to pick-and-place objects in an enviro…
Integrating Task-Motion Planning with Reinforcement Learning for Robust Decision Making in Mobile Robots
Yuqian Jiang, Fangkai Yang, Shiqi Zhang +1
Task-motion planning (TMP) addresses the problem of efficiently generating executable and low-cost task plans in a discrete space such that the (initially unknown) action costs are…
LAAIR: A Layered Architecture for Autonomous Interactive Robots
Yuqian Jiang, Nick Walker, Minkyu Kim +6
When developing general purpose robots, the overarching software architecture can greatly affect the ease of accomplishing various tasks. Initial efforts to create unified robot sy…
Interaction and Autonomy in RoboCup@Home and Building-Wide Intelligence
Justin Hart, Harel Yedidsion, Yuqian Jiang +8
Efforts are underway at UT Austin to build autonomous robot systems that address the challenges of long-term deployments in office environments and of the more prescribed domestic…
An Architecture for Person-Following using Active Target Search
Minkyu Kim, Miguel Arduengo, Nick Walker +4
This paper addresses a novel architecture for person-following robots using active search. The proposed system can be applied in real-time to general mobile robots for learning fea…
Task Planning in Robotics: an Empirical Comparison of PDDL-based and ASP-based Systems
Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal +1
Robots need task planning algorithms to sequence actions toward accomplishing goals that are impossible through individual actions. Off-the-shelf task planners can be used by intel…